Outdoor navigation is widely deployed thanks to the development of various global-navigation satellite-systems (GNSS), e.g., Global Positioning System (GPS), Global Navigation Satellite System (GLONASS) and GALILEO of the European Union (EU) and European Space Agency (ESA). GNSS provide autonomous geo-spatial positioning with global coverage. Small electronic receivers determine their location (longitude, latitude, and altitude) with high precision (within a few meters) using time signals transmitted along a line of sight by radio from satellites.
Recently, there has been a lot of focus on indoor navigation. This field differs from the outdoor navigation since the indoor environment does not enable the reception of signals from GNSS satellites. Rather, a network of devices is used to wirelessly locate objects or people inside a building. The major consumer benefit of indoor positioning is the expansion of location-aware mobile computing indoors. Contextual awareness for applications running on wireless devices has become a priority for developers. Most applications currently rely on GPS, however, and function poorly indoors. Examples of applications benefiting from indoor location include augmented reality, shopping mall, grocery stores and airport maps, targeted advertising, social networking, etc. As a result a lot of effort is being directed towards solving the indoor navigation problem. This problem does not have a scalable solution yet with satisfactory precision.
One solution to this problem is based on the Time-of-Flight (ToF) or Tim-of-Arrival (ToA) method, which is based on the amount of time that a signal takes to propagate from transmitter to receiver. Because the signal propagation rate is constant and known (e.g., ignoring differences in mediums) the travel time of a signal can be used to directly calculate distance. Multiple measurements can be combined with trilateration to find a location. Systems which use ToF generally require a complicated synchronization mechanism to maintain a reliable source of time for sensors. Further, the accuracy of the TOA based methods often suffers from massive multipath conditions in indoor localization, which is caused by the reflection and diffraction of the radio frequency (RF) signal from objects (e.g., interior wall, doors or furniture) in the environment.
ToF methods are very robust and scalable but involve hardware changes to the modems, such as WiFi® modems. Nevertheless, due to the higher accuracy, some new issues arise with ToF location that was insignificant before. Knowing the exact position of the AP is one of these issues. Accurate positioning based on range measurement from access point relies on the knowledge of the position of the access point. The final position accuracy is dependent, among other things, in having the access point position as accurate as the range measurement or better.
The access point's position is available, either within some data base or reported by the access point itself. Bias in the reported access point position will reflect in bias in the determined position of the mobile device. Since the accuracy is quite high (e.g., a few tens of centimeters or less) this task is not simple, and might require dedicated measurement gear such as a total station (The total station is an electronic theodolite integrated with an electronic distance meter) or other. This equipment is typically used by construction surveyors. Targeting high accuracy positioning, for example for shelf accurate navigation, will rely on the accurate determination of the position of access points.